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How Pricing Is Calculated

Wejot generates a live quote from the current survey, audience, screening, quotas, and tracking plan. The subtotal and payment breakdown refresh whenever these inputs change.

Use the payment confirmation as the final quote

This page describes the current standard-survey pricing model. Tag prices and panel supply may change, so the amount shown immediately before payment is authoritative. Advanced screening, quotas, and tracking currently do not apply to AI interview samples.


Formula for one standard survey distribution

common per-complete price = question-count base price + distribution-range tag price + screening / non-attribute quota scarcity price total = common per-complete price × target completes + attribute-quota bucket total

The attribute-quota bucket total is added once and is not multiplied by target count again.

The payment breakdown normally lists question price, targeting tags, screening/scarcity, attribute quota buckets, common unit price, and order total.


1. Question-count base price

Standard surveys use the number of questions to determine the base price per valid complete:

Survey lengthBase price per complete
1–10 questions¥1
11–20¥2
21–30¥3
31–40¥4
41–50¥5
51–60¥6
61–70¥7
71–80¥8
81–300Starts at ¥8; each additional complete block of 10 adds ¥1
More than 300¥30

Removing unnecessary questions can reduce burden and may move the survey into a lower tier.


2. Distribution-range tag price

Distribution range targets profile attributes before invitations are sent:

  • Multiple tags within one attribute category mean “any selected value”; the category uses the lowest selected tag price per complete;
  • Multiple attribute categories must all match, so their category prices are added;
  • An unrestricted attribute adds no targeting fee.

If an attribute is also a quota dimension, that category is removed from range pricing and charged by quota bucket instead, preventing duplicate billing.


3. Screening incidence and fee

Screening rules are converted into an estimated incidence rate. A lower incidence requires more invitations to obtain one qualified complete, raising the per-complete fee.

Estimated incidenceScreening fee per valid complete
100%¥0
80%–99%¥0.50
60%–79%¥1
50%–59%¥2
40%–49%¥3
30%–39%¥4
20%–29%¥6
Below 20%¥12

Respondents who fail do not count as valid completes and are not charged as valid samples. The screening fee is carried by qualified valid completes.

Incidence is an estimate, not a guarantee of collection speed or volume.


4. Quota pricing

Attribute quotas: headcount × tag price per bucket

Attribute buckets must fill their own targets and cannot substitute for one another:

attribute-quota bucket total = sum(bucket headcount × bucket tag unit price)

For percentage quotas:

bucket headcount = round(bucket percentage × total target)

For 100 respondents, 50/50 gender, men at ¥2 and women at ¥1:

Men: 50 × ¥2 = ¥100 Women: 50 × ¥1 = ¥50 Attribute-quota bucket total = ¥150

The ¥150 is added once to the order total.

Survey-answer or custom-screener quotas: scarcity tiers

These answers have no direct tag price, so the narrowest non-zero bucket estimates difficulty:

Narrowest bucket shareWith a screening feeWithout a screening fee
25% or moreNo upliftNo uplift
Below 25%Screening fee × 1.2Add ¥0.60 per complete
Below 10%Screening fee × 1.5Add ¥1.50 per complete

Attribute quotas already use real tag prices and do not receive this scarcity uplift.

When a bucket is full, additional matching responses are screened out and not billed, preserving the purchased structure.


5. Tracking billing

A tracking study locks the common sample unit price at creation. Each later wave applies its incentive multiplier.

wave prepayment = expected count × locked price × multiplier wave settlement = actual valid completes × locked price × multiplier wave refund = max(0, prepayment - settlement)

Pay by wave

  • Pay only for the current wave at creation;
  • Later expected count first uses actual valid completions from the previous wave;
  • Confirm and pay before each later wave opens;
  • Settle on actual valid completes and return excess prepayment to the original method.

Pay all waves upfront

  • Pay the current wave plus estimated future waves together;
  • Future waves without actual data use the final target and retention estimate;
  • Waves open automatically when due;
  • Each wave still settles independently on actual valid completes.

Incentives and replenishment

  • A 1.5× wave multiplies both publisher cost and respondent reward by 1.5;
  • Replenishment beyond the prepaid cap requires an additional payment;
  • Unopened, unpaid waves cost nothing;
  • Canceling a running wave settles completed valid responses and refunds unused prepayment.

6. Valid completes, review, and refunds

Panel service settles on valid completes:

  • Responses that pass screening and quota, finish the survey, and pass quality review are billed;
  • Screening failures and responses rejected because a quota is full are not billed;
  • Responses rejected in quality review do not remain in final valid settlement;
  • Unused distribution budget and unused wave prepayment are refunded against their corresponding orders.

Refunds normally return to the original payment method. Timing depends on the payment channel and the status shown in the product. See Response Review and QA.


Three examples

Ordinary random distribution

20 questions, 100 completes, no targeting, screening, or quota:

unit price = ¥2 question base total = ¥2 × 100 = ¥200

Random distribution with 50/50 gender

20 questions, 100 completes, men at ¥2 and women at ¥1:

common part = ¥2 × 100 = ¥200 gender quota = 50 × ¥2 + 50 × ¥1 = ¥150 total = ¥350

Screening plus a survey-answer quota

20 questions, 100 completes, 45% estimated incidence, and a 20% narrowest question bucket:

question base = ¥2/complete screening fee = ¥3/complete quota-adjusted screening fee = ¥3 × 1.2 = ¥3.60/complete common unit price = ¥2 + ¥3.60 = ¥5.60 total = ¥560

The product calculates the final quote automatically; these examples explain why configuration changes affect it.


Reduce budget without weakening the study

  • Remove questions that do not affect the conclusion;
  • Put profile attributes in distribution range instead of duplicating them as screeners;
  • Keep only rules that truly determine eligibility;
  • Avoid extremely small survey-answer or custom-screener quota buckets;
  • Control only key attribute dimensions;
  • Base tracking retention on prior return data instead of using an unnecessarily low assumption;
  • Review every line in the payment breakdown and pilot at small scale first.
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